Bibliographic record
Abstract
We are now well into 2021, and the COVID-19 vaccination roll-out is in progress, but we are still trying to handle a global pandemic. I hope people take heart from this issue that looks back 100 years, and to the future, to celebrate the discovery of insulin and how this paved the way for saving millions of lives globally. Diabetes is still a disease that has no cure but our knowledge of its biochemistry means it is now manageable and this has transformed the lives of those with the disease within an extremely short period of time.I want to speak about this discovery at the start of this special themed issue. The first use of insulin for treatment of type 1 diabetes in humans was in January 1922, less than 12 months after it had been first successfully extracted by surgeon Sir Frederick Banting and physiologist Charles Best in the labs of Professor John MacLeod at the University of Toronto. James Collip, a Canadian biochemist, had joined the team in Toronto and was able to help concentrate and extract a purer form of insulin from cattle which could then be used in humans.The first treatment involved two injections of insulin that were given to Leonard Thompson, a 14-year-old boy and, for the first time, they were able to lower high blood sugar and he recovered. As is the case with most scientific discoveries, it involved knowledge and input from multiple people to enable people around the world to be treated by insulin. The Nobel Prize was awarded to Banting and Macleod in 1923 with Banting then splitting half of his prize money with Best and Macleod splitting his half with Collip.We are still learning about diabetes today, and with higher numbers of people being diagnosed with type 2 diabetes, it is important to continue the search for a cure for the disease.I am humbled that this is the theme for my first issue of The Biochemist and I want to thank the previous editor Chris Willmott for confirming this as a theme and for his work with The Biochemist over the past few years. The magazine has introduced new features and now has a more easily accessible online presence. I hope that I can maintain the high standard that has been set, and continue to grow the publication.The role of molecular bioscience in society has never been in more focus than it has been over the past 12 months and I want to ensure that The Biochemist continues to highlight the importance of that work.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.093 | 0.051 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".